Quest markup for developing FAIR questionnaire modules for epidemiologic studies

Autor: Daniel E. Russ, Nicole M. Gerlanc, Brian Shen, Bhaumik Patel, Amy Berrington de González, Neal D. Freedman, Julie M. Cusack, Mia M. Gaudet, Montserrat García-Closas, Jonas S. Almeida
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: BMC Medical Informatics and Decision Making, Vol 23, Iss 1, Pp 1-7 (2023)
Druh dokumentu: article
ISSN: 1472-6947
DOI: 10.1186/s12911-023-02338-6
Popis: Abstract Background Online questionnaires are commonly used to collect information from participants in epidemiological studies. This requires building questionnaires using machine-readable formats that can be delivered to study participants using web-based technologies such as progressive web applications. However, the paucity of open-source markup standards with support for complex logic make collaborative development of web-based questionnaire modules difficult. This often prevents interoperability and reusability of questionnaire modules across epidemiological studies. Results We developed an open-source markup language for presentation of questionnaire content and logic, Quest, within a real-time renderer that enables the user to test logic (e.g., skip patterns) and view the structure of data collection. We provide the Quest markup language, an in-browser markup rendering tool, questionnaire development tool and an example web application that embeds the renderer, developed for The Connect for Cancer Prevention Study. Conclusion A markup language can specify both the content and logic of a questionnaire as plain text. Questionnaire markup, such as Quest, can become a standard format for storing questionnaires or sharing questionnaires across the web. Quest is a step towards generation of FAIR data in epidemiological studies by facilitating reusability of questionnaires and data interoperability using open-source tools.
Databáze: Directory of Open Access Journals
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